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Machine Learning Classification with C5.0 Decision Tree Algorithm

Machine Learning Classification with C5.0 Decision Tree Algorithm

We will develop a classification exercise using C5.0 decision tree algorithm. The exercise was originally published in "Machine Learning in R" by Brett Lantz, PACKT publishing 2015 (open source community experience destilled).The example we will develop is about identifying risky bank loans.

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Machine Learning Classification with 1R and RIPPER Rule Learners (Edible/Poisonous Mushrooms)

Machine Learning Classification with 1R and RIPPER Rule Learners (Edible/Poisonous Mushrooms)

We will develop a classification example using 1R and RIPPER rule learners algorithms. The exercise was originally published in "Machine Learning in R" by Brett Lantz, PACKT publishing 2015 (open source community experience destilled).The example we will develop is about classifying edible and poisonous mushrooms.

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Machine Learning Classification Using Naive Bayes

April 28, 2017
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Machine Learning Classification Using Naive Bayes

We will develop a classification exercise using Naive-Bayes algorithm. The exercise was originally published in "Machine Learning in R" by Brett Lantz, PACKT publishing 2015 (open source community experience destilled).Naive Bayes is a probabilistic classification algorithm that can be applied to problems of text classification such as spam filtering, intrusion detection...

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Classification Using Nearest Neighbors k-NN

April 25, 2017
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Classification Using Nearest Neighbors k-NN

We will develop a well-known k-NN exercise originally published in "Machine Learning in R" by Brett Lantz, PACKT publishing 2015.K-nearest neighbors is a classification algorithm and is perhaps one of the simplest machine learning algorithms.The exercise we will develop is: "diagnosing breast cancer with the k-NN algorithm",...

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Function to Simulate Parabolic Shot with Drag.

February 2, 2017
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Function to Simulate Parabolic Shot with Drag.

Script to calculate the most important quantitative information of the drag parabolic shot in International System of Units.If you want to use another system of units you can do it by making some simple changes.This is a first approach to the problem and is totally perfectible.To calculate...

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Function to Simulate Simple Parabolic Shooting.

January 31, 2017
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Function to Simulate Simple Parabolic Shooting.

This function simulates a parabolic shot from the origin and does not take into account the friction of the air.# Script to calculate the most important info about the parabolic# shot without friction and in International System of Units# if you want to use...

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Distribution of Mean of the Combinations of a Set.

January 24, 2017
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Distribution of Mean of the Combinations of a Set.

For some purpose I found myself generating and analyzing the average of the combinations of a set and when I generated the corresponding histogram I was surprised by its shape.It should be remembered that the combinations C(m, n) of a set are the number of ...

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Simulating some synthetic data.

January 12, 2017
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Simulating some synthetic data.

In many cases we require some data with certain characteristics to develop a model, perform research, to test an algorithm or simply to practice.Here I show an example of how to generate some synthetic data that can help you to generate your own.We...

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Exercise to Simulate and Fit a Parabolic Shot.

January 10, 2017
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Exercise to Simulate and Fit a Parabolic Shot.

In this exercise we assume that we obtained the measurements of the height and the distance of the movement of a projectile by means of an experiment.We define the vectors "Height" and "Distance" that have our physical measurements.We fit a second-order model "lmr".

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Function to create an amortization fund table in R

January 3, 2017
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Function to create an amortization fund table in R

Function to create an amortization fund table.We establish the precision with which we want to work options(digits = 7)we say we do not want to work in scientific notation  options(scipen = 999) We declare vectors to store the values of the different variablesI <- numeric();CA <<- numeric();SF <<- numeric() We give values for the amount, number of periods and...

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